No abstract is provided for this article.
No abstract is provided for this article.
No abstract is provided for this article.
In one of our recent publications [1], a formula for the computation of the strain energy release rate from 3-D singularity finite elements was derived based on the Irwin's Crack Closure Integral (ICCI) method. In this paper, the stress intensity factors of embedded elliptical and semi-elliptical surface cracks in a finite thickness plate subjected to tension are calculated using this formula. Comparisons between the numerical results obtained using the formula and those from the literature [2,3] showed that the proposed technique yields accurate stress intensity factors.
In Structural Health Monitoring (SHM) of bridges, accurately assessing damage is critical to maintaining the safety and integrity of a structure. One of the primary challenges in damage assessment is the precise localization and quantification of defects, which is essential for making timely maintenance decisions and reducing the risk of structural failures. This paper introduces a novel damage detection method for SHM of a truss bridge by coupling a Deep Neural Network (DNN) model with an evolved Artificial Rabbit Optimization (EVARO) algorithm. The integration of DNN with the stochastic search capability of the EVARO algorithm helps to avoid local minima, thereby ensuring more accurate and reliable results. Additionally, the optimization algorithm’s effectiveness is further enhanced by incorporating evolving predator features and the Cauchy motion search mechanism. The proposed method is first validated using various data benchmark problems, demonstrating its effectiveness compared to other well-known algorithms. Secondly, a case study involving the Chuong Duong truss bridge under different simulated damage scenarios further confirms the superiority of the proposed method in both localizing and quantifying damages.
No abstract is provided for this article.
No abstract is provided for this article.
No abstract is provided for this article.
When considering the sound transmission through a wall in between two rooms, in an important part of the audio frequency range, the local response of the rooms is highly sensitive to uncertainty in spatial variations in geometry, material properties and boundary conditions, which have a wave scattering effect, while the local response of the wall is rather insensitive to such uncertainty. For this mid-frequency range, a computationally efficient modeling strategy is adopted that accounts for this uncertainty. The partitioning wall is modeled deterministically, e.g. with finite elements. The rooms are modeled in a very efficient, nonparametric stochastic way, as in statistical energy analysis. All components are coupled by means of a rigorous power balance. This hybrid strategy is extended so that the mean and variance of the sound transmission loss can be computed as well as the transition frequency that loosely marks the boundary between low- and high-frequency behavior of a vibro-acoustic component. The method is first validated in a simulation study, and then applied for predicting the airborne sound insulation of a series of partition walls of increasing complexity: a thin plastic plate, a wall consisting of gypsum blocks, a thicker masonry wall and a double glazing. It is found that the uncertainty caused by random scattering is important except at very high frequencies, where the modal overlap of the rooms is very high. The results are compared with laboratory measurements, and both are found to agree within the prediction uncertainty in the considered frequency range.
The use of the substructuring technique for the solution of two-dimensional non-linear problems of dynamic response with the direct time integration method is examined. The object is to develop schemes that can considerably reduce the computational expense in analyses of locally and fully non-linear dynamic problems as compared with a traditional analysis. After a review of the principle of the incremental equilibrium equations of motion, some practical illustrations of the technique are dealt with in detail. A specific flow chart is proposed and a number of numerical examples are presented.
When considering a wall in between two rooms, in an important part of the audio frequency range the local response of the rooms may be highly sensitive to uncertainty in spatial variations in geometry, material properties, boundary conditions, etc, while the local response of the wall is rather insensitive to such uncertainty. For this mid-frequency problem, a hybrid strategy is adopted that accounts for the uncertainty in the local room properties. The partition is modeled deterministically, with finite elements. The rooms are modeled in a very efficient, nonparametric stochastic way, as in statistical energy analysis. This strategy is extended so that not only the mean value of the sound transmission loss, but also the variance can be computed. A second extension allows computing band-averaged quantities in an efficient way. The method is then applied to a set of partitions of increasing complexity: a thin PMMA plate, a wall consisting of gypsum blocks and a thicker masonry wall. The results are compared with laboratory measurements, and it is found that the uncertainty caused by the random local room properties is well captured.
